High rate acoustic communications based on orthogonal frequency division multiplexing

2008 ◽  
Vol 123 (5) ◽  
pp. 3891-3891 ◽  
Author(s):  
Milica Stojanovic
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
High Rate ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Acoustic Communications

Peak-to-Average Power Ratio Reduction for Acoustic Orthogonal Frequency Division Multiplexing Systems

2010 ◽  
Vol 44 (4) ◽  
pp. 30-41 ◽  
Author(s):  
Guillem Rojo ◽  
Milica Stojanovic
Keyword(s):  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multipath Propagation ◽  
Average Power ◽  
Gradient Algorithm ◽  
High Rate ◽  
Modulation Scheme ◽  
Frequency Division Multiplexing ◽  
Power Ratio ◽  
Frequency Division

AbstractOrthogonal frequency division multiplexing (OFDM) is an appealing modulation scheme for high-rate underwater acoustic communications that are challenged by multipath propagation. However, it has a drawback in the large peak-to-average power ratio (PAR). Techniques for PAR reduction have been extensively studied for radio communication systems. Although these techniques are applicable to acoustic systems, we take a different approach that aims to capitalize on the fundamental differences between the acoustic and the radio systems; namely, the fact that acoustic transmissions are inherently band limited. We extend the tone reservation technique to the out-of-band carriers and design efficient methods for constructing OFDM signals with lower PAR. Two approaches are investigated, one based on a gradient algorithm and another that uses random sequences. Simulation results show that our techniques can provide PAR reduction without the loss in data rate.

scholarly journals Iterative Learning for Reliable Underwater Link Adaptation (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13761-13762
Author(s):  
Junghun Byun ◽  
Yong-Ho Cho ◽  
Tae-Ho Im ◽  
Hak-Lim Ko ◽  
Kyung-Seop Shin ◽  
...  
Keyword(s):  
Performance Improvement ◽  
Orthogonal Frequency Division Multiplexing ◽  
Link Adaptation ◽  
Learning Model ◽  
Iterative Learning ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Acoustic Communications ◽  
Learning Framework ◽  
First Time

This paper describes an iterative learning framework consisting of multi-layer prediction processes for underwater link adaptation. To obtain a dataset in real underwater environments, we implemented OFDM (Orthogonal Frequency Division Multiplexing)-based acoustic communications testbeds for the first time. Actual underwater data measured in Yellow Sea, South Korea, were used for training the iterative learning model. Remarkably, the iterative learning model achieves up to 25% performance improvement over the conventional benchmark model.

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